update the image classification markdown

03.image_classification/README.md

@@ -328,6 +328,15 @@ def train_program():
     return [avg_cost, accuracy]
 ```
 
+## Optimizer Function Configuration
+
+In the following `Adam` optimizer, `learning_rate` specifies the learning rate in the optimization procedure.
+
+```python
+def optimizer_program():
+    return fluid.optimizer.Adam(learning_rate=0.001)
+```
+
 ## Model Training
 
 ### Create Trainer
@@ -340,7 +349,7 @@ use_cuda = False
 place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 trainer = fluid.Trainer(
     train_func=train_program,
-    optimizer=fluid.optimizer.Adam(learning_rate=0.001),
+    optimizer_func=optimizer_program,
     place=place)
 ```
 

03.image_classification/index.html

@@ -370,6 +370,15 @@ def train_program():
     return [avg_cost, accuracy]
 ```
 
+## Optimizer Function Configuration
+
+In the following `Adam` optimizer, `learning_rate` specifies the learning rate in the optimization procedure.
+
+```python
+def optimizer_program():
+    return fluid.optimizer.Adam(learning_rate=0.001)
+```
+
 ## Model Training
 
 ### Create Trainer
@@ -382,7 +391,7 @@ use_cuda = False
 place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 trainer = fluid.Trainer(
     train_func=train_program,
-    optimizer=fluid.optimizer.Adam(learning_rate=0.001),
+    optimizer_func=optimizer_program,
     place=place)
 ```
 

03.image_classification/train.py

@@ -42,6 +42,10 @@ def train_network():
     return [avg_cost, accuracy]
 
 
+def optimizer_program():
+    return fluid.optimizer.Adam(learning_rate=0.001)
+
+
 def train(use_cuda, train_program, params_dirname):
     BATCH_SIZE = 128
     EPOCH_NUM = 2
@@ -74,9 +78,7 @@ def train(use_cuda, train_program, params_dirname):
 
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
     trainer = fluid.Trainer(
-        train_func=train_program,
-        optimizer=fluid.optimizer.Adam(learning_rate=0.001),
-        place=place)
+        train_func=train_program, optimizer_func=optimizer_program, place=place)
 
     trainer.train(
         reader=train_reader,